Portfolio Selection Models Based on Interval-Valued Conditional Value-at-Risk (ICVaR) and Case Study on the Data from Stock Markets

Risk management is very important for individual investors or companies. There are several ways to measure the risk of investment. Prices of risky assets vary rapidly and randomly due to the complexity of finance market. Random interval is a good tool to describe uncertainty including both randomnes...

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Bibliographic Details
Published in:Fractal and fractional 2022-10, Vol.6 (10), p.536
Main Authors: Zhang, Jinping, Zhang, Keming
Format: Article
Language:English
Subjects:
Capital assets
Case studies
conditional value-at-risk (CVaR)
Financing
interval-valued random variable
Investments
Linear programming
Optimization
portfolio selection
Prices
Project evaluation
R&D
Random variables
Research & development
Risk management
Securities markets
Stock exchanges
Uncertainty
value-at-risk (VaR)
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Summary:Risk management is very important for individual investors or companies. There are several ways to measure the risk of investment. Prices of risky assets vary rapidly and randomly due to the complexity of finance market. Random interval is a good tool to describe uncertainty including both randomness and imprecision. Considering the uncertainty of financial market, we employ random intervals to describe returns of a risk asset and define an interval-valued risk measurement, which considers the tail risk. It is called the interval-valued conditional value-at-risk (ICVaR, for short). Similar to the classical conditional value-at-risk, ICVaR satisfies the sub-additivity. Under the new risk measure ICVaR, as a manner similar to the classical Mean-CVaR portfolio model, two optimal interval-valued portfolio selection models are built. The sub-additivity of ICVaR guarantees the global optimal solution to the Mean-ICVaR portfolio model. Based on the real data from mainland Chinese stock markets and international stock markets, the case study shows that our models are interpretable and consistent with the practical scenarios.
ISSN:2504-3110
2504-3110
DOI:10.3390/fractalfract6100536